On 11/29/2012 01:37 AM, Mark Hahn wrote:
>> "consumer" products. And then, there's the "Win on Sunday, sell on
>> Monday" effect, which I don't think needs any explanation.
> there's a premise here which I think is mistaken. this theory depends
> on the F1 circuit having a very different cost-effectiveness requirement.
> that team X will spend whatever it takes to gain an advantage, and
> that once developed, the advantage can transfer to consumer products.
> does exascale really have a blank check to develop exotic whatever-it-takes
> technologies? in a very meaningful sense, HPC is all about
> cost-effectiveness, even at high scale. you want a computer 10x faster
> so you don't have to wait as long - there's no whatever-it-takes there.
I'm going to stick to my guns here. For people doing HPC 'in the
trenches' I think cost-effectiveness is important (and the smaller your
budget, the more important it gets), but I wouldn't say HPC is 'all
about that'. And at the top of the Top500 list is, which is what we are
talking about (exascale, remember), I don't think cost-effectiveness is
the number #1 priority. The K Computer cost $1.25 billion USD to design
and build. That was backed by the Japanese government. China's been
spending a lot of money developing super computers and their own
processors. In both of these cases, these have been whatever-it-takes
efforts, backed by national governments.
In the US, I think there is currently a bit more of a cost-effective
mentality, even at the Top of the Top500 list, as evidenced by IBM
pulling out of Blue Waters because they didn't think it was going to be
profitable for them to continue.
And then there's all those classified systems we don't know about being
used by the 3-letter organizations of the US government. I'm sure they
are designed using whatever-it-takes technologies. But they're aren't
relevant to the "Win on Sunday..." argument since no one really knows
what they are or can do, and we definitely don't know if they're winning.
>>> An even more cynical view say that the HPC vendors lobby the government
>> to believe exascale is important so the government invests in it and
>> subsidizes their R&D.
> oh, I don't think that's a stretch at all. governments love to be sold
> on the idea that they're special and because of that, they need to invest
> in preservation of that specialness. one word: military.
>>> In my opinion, the new technology driven by the move to petscale,
>> exascle, etc, will ultimately valuable to use consumers, but to your
> I claim that tech is largely fungible these days. chip-stacking
> was first mass-produced for phones afaik. but anyone who wants to do it
> can just buy some expertise or just outsource to get it done.
> the trick is in how you put the pieces together.
>>> average researcher, having a decent-sized cluster that they have a lot
>> of access to is more valuable than a large, shared system like Blue
>> Waters or something similar, that must shared with hundreds or thousands
>> of other researchers.
> well, that's stretching things a lot. some people have steady workloads,
> and for them, owning dedicated hardware makes the most sense. most people,
> though, have bursty demand, and sharing large resource pools is ideal.
> but "large resource pool" has nothing to do with exascale - the size of
> your shared machines is really a question of average job sizes and minimizing
> fragmentation. (so, for instance, if I had money to spend on 1M cores,
> I'd definitely spend most of it on clusters of a few hundred nodes -
> say, O(10k) cores.)
I wasn't saying that the researched would own their own hardware, just
that it's probably more useful to your average researcher to have a
smaller system shared by less people that they can get more cpu-hours on
and access more easily (A university-wide HPC center, for example).
>> I think your negative reference to big-shared systems is actually more
> a comment on how big systems seem to inspire BOFHishness - that it's
> hard to get access to them. their keepers quite naturally incline
> toward a job mix that shows off the biggness to its best advantage.
> "I successfully argued to spend extra to make it big, so I don't want
> it overcome with hordes of mundane-sized jobs!" unfortunately this
> seems to go along with the kind of foot-dragging that gives us application
> processes that cycle at 1/year (here in Canada at least, not that we have
> decent non-spasmodic HPC funding...)
Actually, that opinion was based on my conversations with a couple of
prominent computational scientists at national labs, but you raise
excellent points about BOFHisness. and the application process, which I
wasn't even considering.
--
Prentice